38 research outputs found
MeDICINE: Rapid Prototyping of Production-Ready Network Services in Multi-PoP Environments
Virtualized network services consisting of multiple individual network
functions are already today deployed across multiple sites, so called multi-PoP
(points of presence) environ- ments. This allows to improve service performance
by optimizing its placement in the network. But prototyping and testing of
these complex distributed software systems becomes extremely challenging. The
reason is that not only the network service as such has to be tested but also
its integration with management and orchestration systems. Existing solutions,
like simulators, basic network emulators, or local cloud testbeds, do not
support all aspects of these tasks. To this end, we introduce MeDICINE, a novel
NFV prototyping platform that is able to execute production-ready network func-
tions, provided as software containers, in an emulated multi-PoP environment.
These network functions can be controlled by any third-party management and
orchestration system that connects to our platform through standard interfaces.
Based on this, a developer can use our platform to prototype and test complex
network services in a realistic environment running on his laptop.Comment: 6 pages, pre-prin
Deploying elastic routing capability in an SDN/NFV-enabled environment
SDN and NFV are two paradigms that introduce unseen flexibility in telecom networks. Where previously telecom services were provided by dedicated hardware and associated (vendor-specific) protocols, SDN enables to control telecom networks through specialized software running on controllers. NFV enables highly optimized packet-processing network functions to run on generic/multi-purpose hardware such as x86 servers. Although the possibilities of SDN and NFV are well-known, concrete control and orchestration architectures are still under design and few prototype validations are available. In this demo we demonstrate the dynamic up-and downscaling of an elastic router supporting NFV-based network management, for example needed in a VPN service. The framework which enables this elasticity is the UNIFY ESCAPE environment, which is a PoC following an ETSI NFV MANO-conform architecture. This demo is one of the first to demonstrate a fully closed control loop for scaling NFs in an SDN/NFV control and orchestration architecture
Introducing Development Features for Virtualized Network Services
Network virtualization and softwarizing network functions are trends aiming
at higher network efficiency, cost reduction and agility. They are driven by
the evolution in Software Defined Networking (SDN) and Network Function
Virtualization (NFV). This shows that software will play an increasingly
important role within telecommunication services, which were previously
dominated by hardware appliances. Service providers can benefit from this, as
it enables faster introduction of new telecom services, combined with an agile
set of possibilities to optimize and fine-tune their operations. However, the
provided telecom services can only evolve if the adequate software tools are
available. In this article, we explain how the development, deployment and
maintenance of such an SDN/NFV-based telecom service puts specific requirements
on the platform providing it. A Software Development Kit (SDK) is introduced,
allowing service providers to adequately design, test and evaluate services
before they are deployed in production and also update them during their
lifetime. This continuous cycle between development and operations, a concept
known as DevOps, is a well known strategy in software development. To extend
its context further to SDN/NFV-based services, the functionalities provided by
traditional cloud platforms are not yet sufficient. By giving an overview of
the currently available tools and their limitations, the gaps in DevOps for
SDN/NFV services are highlighted. The benefit of such an SDK is illustrated by
a secure content delivery network service (enhanced with deep packet inspection
and elastic routing capabilities). With this use-case, the dynamics between
developing and deploying a service are further illustrated
VNF performance modelling : from stand-alone to chained topologies
One of the main incentives for deploying network functions on a virtualized or cloud-based infrastructure, is the ability for on-demand orchestration and elastic resource scaling following the workload demand. This can also be combined with a multi-party service creation cycle: the service provider sources various network functions from different vendors or developers, and combines them into a modular network service. This way, multiple virtual network functions (VNFs) are connected into more complex topologies called service chains. Deployment speed is important here, and it is therefore beneficial if the service provider can limit extra validation testing of the combined service chain, and rely on the provided profiling results of the supplied single VNFs. Our research shows that it is however not always evident to accurately predict the performance of a total service chain, from the isolated benchmark or profiling tests of its discrete network functions. To mitigate this, we propose a two-step deployment workflow: First, a general trend estimation for the chain performance is derived from the stand-alone VNF profiling results, together with an initial resource allocation. This information then optimizes the second phase, where online monitored data of the service chain is used to quickly adjust the estimated performance model where needed. Our tests show that this can lead to a more efficient VNF chain deployment, needing less scaling iterations to meet the chain performance specification, while avoiding the need for a complete proactive and time-consuming VNF chain validation
Adaptive & learning-aware orchestration of content delivery services
Many media services undergo a varying workload, showing periodic usage patterns or unexpected traffic surges. As cloud and NFV services are increasingly softwarized, they enable a fully dynamic deployment and scaling behaviour. At the same time, there is an increasing need for fast and efficient mechanisms to allocate sufficient resources with the same elasticity, only when they are needed. This requires adequate performance models of the involved services, as well as awareness of those models in the involved orchestration machinery. In this paper we present how a scalable content delivery service can be deployed in a resource- and time-efficient manner, using adaptive machine learning models for performance profiling. We include orchestration mechanisms which are able to act upon the profiled knowledge in a dynamic manner. Using an offline profiled performance model of the service, we are able to optimize the online service orchestration, requiring fewer scaling iterations
NFV service dynamicity with a DevOps approach : demonstrating zero-touch deployment & operations
Next generation network services will be realized by NFV-based microservices to enable greater dynamics in deployment and operations. Here, we present a demonstrator that realizes this concept using the NFV platform built in the EU FP7 project UNIFY. Using the example of an Elastic Router service, we show automated deployment and configuration of service components as well as corresponding monitoring components facilitating automated scaling of the entire service. We also demonstrate automatic execution of troubleshooting and debugging actions. Operations of the service are inspired by DevOps principles, enabling quick detection of operational conditions and fast corrective actions. This demo conveys essential insights on how the life-cycle of an NFV-based network service may be realized in future NFV platforms